Surface roughness prediction model of 6061-T6 aluminium alloy machining using statistical method

dc.contributor.authorKadirgama, K.
dc.contributor.authorNoor, M.M.
dc.contributor.authorRahman, M.M.
dc.contributor.authorRejab, M.R.M.
dc.contributor.authorHaron, C.H.C.
dc.contributor.authorAbou-El-Hossein, Khaled A.
dc.contributor.emailKhaled.abou-el-hossein@up.ac.zaen
dc.date.accessioned2010-04-06T07:08:39Z
dc.date.available2010-04-06T07:08:39Z
dc.date.issued2009
dc.description.abstractThis paper explores on the optimization of the surface roughness of milling mould 6061-T6 aluminium alloys with carbide coated inserts. Optimization of the milling is very important to reduce the cost and time for machining mould. The purposes of this study are to develop the predicting model of surface roughness, to investigate the most dominant variables among the cutting speed, feed rate, axial depth and radial depth and to optimize Surface Roughness Prediction Model of 6061-T6 Aluminium Alloy Machining Using Statistical Method the parameters. Response surface method based optimization approach was used in this study. It can be seen from the first order model that the feed rate is the most significantly influencing factor for the surface roughness. Second-order model reveals that there is no interaction between the variables and response.en
dc.identifier.citationKadirgama, K, Noor, MM, Rahman, MM, Rejab, MRM, Haron, CHC & Abou-El-Hossein, KA, 'Surface roughness prediction model of 6061-T6 aluminium alloy machining using statistical method', European Journal of Scientific Research, vol. 25, no. 2, pp. 250-256. [http://www.eurojournals.com/EJSR.htm]en
dc.identifier.issn1450-216X
dc.identifier.urihttp://hdl.handle.net/2263/13788
dc.language.isoenen
dc.publisherEuro Journalsen
dc.rightsEuro Journalsen
dc.subject.lcshSurface roughness -- Forecastingen
dc.subject.lcshResponse surfaces (Statistics)en
dc.subject.lcshMachiningen
dc.subject.lcshAluminum alloysen
dc.subject.lcshMilling (Metal-work)en
dc.subject.lcshMetal-cuttingen
dc.subject.lcshMathematical optimizationen
dc.titleSurface roughness prediction model of 6061-T6 aluminium alloy machining using statistical methoden
dc.typeArticleen

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